Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA
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SciScore for 10.1101/2020.08.14.20175190: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study also has limitations. Despite the matching and use of various comparison cohorts, there may be residual confounding. There is little information in the network regarding social and economic factors which might influence clinical outcomes post COVID-19. We do not know whether psychiatric diagnoses were made correctly and …
SciScore for 10.1101/2020.08.14.20175190: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The study also has limitations. Despite the matching and use of various comparison cohorts, there may be residual confounding. There is little information in the network regarding social and economic factors which might influence clinical outcomes post COVID-19. We do not know whether psychiatric diagnoses were made correctly and consistently between cohorts; it is possible that clinicians were more likely to diagnose a psychiatric illness after a COVID-19 diagnosis due to subjective bias. We did not examine whether COVID-19 affects relapse rate in those with prior psychiatric disorder. The results cannot necessarily be generalised to other populations or healthcare settings. Nevertheless, the findings are of sufficient robustness and magnitude to have some immediate implications. The figures provide minimum estimates of the excess in psychiatric morbidity to be anticipated in survivors of COVID-19 and for which services need to plan29. As COVID-19 sample sizes and survival times increase, it will be possible not only to refine these findings, but also to identify rarer and delayed psychiatric presentations. It will also be important to explore additional risk factors for contracting COVID-19, and for developing psychiatric illness thereafter, since some elements may prove to be modifiable.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2020.08.14.20175190: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement TriNetX has a waiver from the Western Institutional Review Board since only de-identified summary statistics are provided. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
The study also has limitations. Despite the matching and use of various comparison cohorts, there may be residual …
SciScore for 10.1101/2020.08.14.20175190: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement TriNetX has a waiver from the Western Institutional Review Board since only de-identified summary statistics are provided. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
The study also has limitations. Despite the matching and use of various comparison cohorts, there may be residual confounding. There is little information in the network regarding social and economic factors which might influence clinical outcomes post COVID-19. We do not know whether psychiatric diagnoses were made correctly and consistently between cohorts; it is possible that clinicians were more likely to diagnose a psychiatric illness after a COVID-19 diagnosis due to subjective bias. We did not examine whether COVID-19 affects relapse rate in those with prior psychiatric disorder. The results cannot necessarily be generalised to other populations or healthcare settings. Nevertheless, the findings are of sufficient robustness and magnitude to have some immediate implications. The figures provide minimum estimates of the excess in psychiatric morbidity to be anticipated in survivors of COVID-19 and for which services need to plan29. As COVID-19 sample sizes and survival times increase, it will be possible not only to refine these findings, but also to identify rarer and delayed psychiatric presentations. It will also be important to explore additional risk factors for contracting COVID-19, and for developing psychiatric illness thereafter, since some elements may prove to be modifiable.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.
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